Computer Science ›› 2019, Vol. 46 ›› Issue (2): 315-320.doi: 10.11896/j.issn.1002-137X.2019.02.048

• Interdiscipline & Frontier • Previous Articles     Next Articles

Social Team Formation Method Based on Fuzzy Multi-objective Evolution

JIN Ting1, TAN Wen-an1,2, SUN Yong1, ZHAO Yao1   

  1. School of Computer Science and Technology,Nanjing University of Aeronautics and Astronautics,Nanjing 211106,China1
    School of Computer and Information Engineering,Shanghai Polytechnic University,Shanghai 201029,China2
  • Received:2017-12-07 Online:2019-02-25 Published:2019-02-25

Abstract: The present team formation researches in social network mostly take 0-1 rule to measure expert skills.Aiming at the situation that people often utilize the natural language to describe expert skills,this paper proposed a social team formation method based on fuzzy multi-objective evolution.This method focuses on how to find out the appropriate individuals from the expert social network to form a team with certain size and achieves the optimization between communication cost and team performance under the uncertainty circumstances.In this method,the precise parameters represented by 0-1 rule are replaced by fuzzy language variables to describe expert skill.The concept of team performance is used to measure team capability.Because the standard SPEA2 algorithm has slow convergence at the initialevolutio-nary stage,this paper introduced AEL strategy to generate individuals with good characteristics.Considering the ambi-guity of expert skills,this paper also proposed a fine-grained Dominance judgment as the new rule of judging the dominance relationship of individuals.The simulation results show that the improved algorithm converges fast and obtains good quality approximate PF,which can be successfully applied to solve the team formation problem.

Key words: Social network, Team formation, Fuzzy language variables, Evolutionary algorithm

CLC Number: 

  • TP311
[1]LAPPAS T,LIU K,TERZI E.Finding a team of experts in social networks[C]∥Proceedings of the 15th ACM SIGKDD International Conf. on Knowledge Discovery and Data Mining.New York:ACM,2009:467-476.
[2]LI C T,SHAN M K.Team formation for generalized tasks in expertise social networks[C]∥Proceedings of IEEE International Conference on Social Computing.Piscataway,NJ:IEEE,2010:9-16.
[3]KARGAR M,AN A.Discovering top-k teams of experts with/without a leader in social networks[C]∥Proceedings of the 20th ACM International Conference on Information and Knowledge Management.New York:ACM,2011:985-994.
[4]KARGAR M,ZIHAYAT M,AN A.Finding affordable and collaborative teams from a network of experts[C]∥Proceedings of the 13th SIAM International Conference on Data Mining.2013:587-595.
[5]KARGAR M,AN A,ZIHAYAT M.Efficient Bi-objective Team Formation in Social Networks[C]∥Proceedings of 2012 European Conference on Machine Learning & Knowledge Discovery in Databases.Berlin:Springer-Verlag,2012:483-498.
[6]SUN Y,TAN W A,LI L,et al.A new method to identify colla- borative partners in social service provider networks[J].Information Systems Frontiers,2016,18(3):565-578.
[7]SUN Y,TAN W A.Cross-Organizational Workflow Task Allocation Algorithms for Socially Aware Collaborative Computing[J].Journal of Computer Research and Development,2017,54(9):1865-1879.(in Chinese)
孙勇,谭文安.支持社会协同计算的跨组织工作流任务分派算法[J].计算机研究与发展,2017,54(9):1865-1879.
[8]SUN H L,JIN M Y,LIU J L,et al.Methods for Team Formation Problem with Grouping Task in Social Networks[J].Journal of Computer Research and Development,2015,52(11):2535-2544.(in Chinese)
孙焕良,金洺宇,刘俊岭,等.社会网络上支持任务分组的团队形成方法[J].计算机研究与发展,2015,52(11):2535-2544.
[9]FARHADI F,SORKHI M,HASHEMI S,et al.An effective expert team formation in social networks based on skill grading[C]∥Proceedings of 2011 IEEE 11th International Conference on Data Mining Workshops (ICDMW).New York:IEEE,2011:366-372.
[10]SUN H L,FU S S,LIU J L,et.al.Team Formation with Weak Ties in Social Networks[J].Journal of Frontiers of Computer Science and Technology,2016,10(6):773-785.(in Chinese)
孙焕良,富珊珊,刘俊岭,等.社会网络中弱关系团队形成问题研究[J].计算机科学与探索,2016,10(6):773-785.
[11]XIE C W,WANG Z J,XIA X W.Multi-Objective Evolutionary Algorithm Based on Archive-Elite Learning and Opposition-Based Learning[J].Chinese Journal of Computers,2017,40(3):757-772.(in Chinese)
谢承旺,王志杰,夏学文.应用档案精英学习和反向学习的多目标进化算法[J].计算机学报,2017,40(3):757-772.
[12]BAYKASOGLU A,DERELI T,DAS S.Project team selection using fuzzy optimization approach[J].Cybernetics and Systems,2007,38(2):155-185.
[1] SUN Yong-yue, LI Hong-yan, ZHANG Jin-bo. RAISE:Efficient Influence Cost Minimizing Algorithm in Social Network [J]. Computer Science, 2019, 46(9): 59-65.
[2] LIU Xiao-jie, LV Xiao-qiang, WANG Xiao-ling, ZHANG Wei, ZHAO An. Mining User Interests on Twitter Using Wikipedia Category Graph [J]. Computer Science, 2019, 46(9): 79-84.
[3] ZHANG Zheng, WANG Hong-zhi, DING Xiao-ou, LI Jian-zhong, GAO Hong. Identification of Same User in Social Networks [J]. Computer Science, 2019, 46(9): 93-98.
[4] SHI Jun-ling,WANG Xing-wei,HUANG Min. Content-centric Routing Scheme in Vehicular Social Networks [J]. Computer Science, 2019, 46(7): 50-55.
[5] LIU Chang-yun,YANG Yu-di,ZHOU Li-hua,ZHAO Li-hong. Discovering Popular Social Location with Time Label [J]. Computer Science, 2019, 46(7): 186-194.
[6] LV Zhi-quan, LI Hao, ZHANG Zong-fu, ZHANG Min. Topic-based Re-identification for Anonymous Users in Social Network [J]. Computer Science, 2019, 46(6): 143-147.
[7] GENG Huan-tong, HAN Wei-min, ZHOU Shan-sheng, DING Yang-yang. MOEA/D Algorithm Based on New Neighborhood Updating Strategy [J]. Computer Science, 2019, 46(5): 191-197.
[8] YUAN De-yu, GAO Jian, YE Meng-xi, WANG Xiao-juan,. Malicious Information Source Locating Algorithm Based on Topological Extension in Online Social Network [J]. Computer Science, 2019, 46(5): 129-134.
[9] HUANG Jian-yi, LI Jian-jiang, WANG Zheng, FANG Ming-zhe. Single-Pass Short Text Clustering Based on Context Similarity Matrix [J]. Computer Science, 2019, 46(4): 50-56.
[10] HAN Zhong-ming, ZHENG Chen-ye, DUAN Da-gao, DONG Jian. Associated Users Mining Algorithm Based on Multi-information Fusion Representation Learning [J]. Computer Science, 2019, 46(4): 77-82.
[11] WU Jie-hua,SHEN Jing,ZHOU Bei. Community Features Based Balanced Modularity Maximization Social Link Prediction Model [J]. Computer Science, 2019, 46(3): 253-259.
[12] ZHAO Qian-qian, LV Min, XU Yin-long. Estimating Graphlets via Two Common Substructures Aware Sampling in Social Networks [J]. Computer Science, 2019, 46(3): 314-320.
[13] XU Fang, DENG Min, XIONG Zeng-gang, YE Cong-huan, XU Ning. Data Forwarding Algorithm Based on Multidimensional Context Matching in Mobile Social Networks [J]. Computer Science, 2019, 46(2): 81-87.
[14] CHEN Jiong, ZHANG Hu, CAO Fu-yuan. Study on Point-of-interest Collaborative Recommendation Method Fusing Multi-factors [J]. Computer Science, 2019, 46(10): 77-83.
[15] ZHOU Yi-hua, ZHANG Bing, YANG Yu-guang, SHI Wei-min. Cluster-based Social Network Privacy Protection Method [J]. Computer Science, 2019, 46(10): 154-160.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
[1] . [J]. Computer Science, 2018, 1(1): 1 .
[2] LEI Li-hui and WANG Jing. Parallelization of LTL Model Checking Based on Possibility Measure[J]. Computer Science, 2018, 45(4): 71 -75, 88 .
[3] XIA Qing-xun and ZHUANG Yi. Remote Attestation Mechanism Based on Locality Principle[J]. Computer Science, 2018, 45(4): 148 -151, 162 .
[4] LI Bai-shen, LI Ling-zhi, SUN Yong and ZHU Yan-qin. Intranet Defense Algorithm Based on Pseudo Boosting Decision Tree[J]. Computer Science, 2018, 45(4): 157 -162 .
[5] WANG Huan, ZHANG Yun-feng and ZHANG Yan. Rapid Decision Method for Repairing Sequence Based on CFDs[J]. Computer Science, 2018, 45(3): 311 -316 .
[6] SUN Qi, JIN Yan, HE Kun and XU Ling-xuan. Hybrid Evolutionary Algorithm for Solving Mixed Capacitated General Routing Problem[J]. Computer Science, 2018, 45(4): 76 -82 .
[7] ZHANG Jia-nan and XIAO Ming-yu. Approximation Algorithm for Weighted Mixed Domination Problem[J]. Computer Science, 2018, 45(4): 83 -88 .
[8] WU Jian-hui, HUANG Zhong-xiang, LI Wu, WU Jian-hui, PENG Xin and ZHANG Sheng. Robustness Optimization of Sequence Decision in Urban Road Construction[J]. Computer Science, 2018, 45(4): 89 -93 .
[9] LIU Qin. Study on Data Quality Based on Constraint in Computer Forensics[J]. Computer Science, 2018, 45(4): 169 -172 .
[10] ZHONG Fei and YANG Bin. License Plate Detection Based on Principal Component Analysis Network[J]. Computer Science, 2018, 45(3): 268 -273 .